All Nippon Airways (ANA) is Japan's largest airline, operating domestic and international routes. ANA has been awarded the "5-Star Airline" rating from SKYTRAX World Airline Rating for six consecutive years, and is the first Japanese airline to do so.

As a part of ANA's five-year growth strategy, the company aims to achieve sustainable growth during the period leading up to the 2020 Tokyo Olympic and Paralympic Games and beyond. Its three key strategies are: expand airline revenue platform and pursue optimized portfolio, select and concentrate on existing business and create new business domains, and utilize open innovation and digital technologies.

“We will create value by integrating ANA's big data into digital technologies such as artificial intelligence, including machine learning and internet of things," says Hajime Fudeshima, director of Business Intelligence, Innovation, and IT Strategy at ANA.

ANA's on-premises data-analysis platform has recently faced some problems that have driven the company to consider other IT options. These include limited disk capacity, long in-batch processing time, and increasing loads on system operation.

"It was difficult to accumulate new data due to limited disk capacity, so we were not able to do sophisticated data analysis," says Naoki Ishii, manager of Data Management Systems Migration Project at ANA Systems.

"The key factors behind choosing AWS were the high level of security demonstrated by organizations in Japan such as financial and retail businesses--all of which deal with a large volume of confidential information--and the number of AWS partners with relevant expertise being overwhelmingly large," says Fudeshima.

The migration project began in October 2016 and the system was launched in February 2018. ANA used the AWS Database Migration Service (AWS DMS) and was able to migrate the on-premises data-analysis platform used for more than 20 years to the cloud without any major issues.

By taking advantage of AWS's professional consulting services and incorporating expert knowledge from the beginning, ANA's migration progressed smoothly. "By having information on Amazon Redshift, our decision-making speed was accelerated. As a result, this contributed greatly to project quality, cost, and delivery times," says Fudeshima.

Fudeshima says ANA has been able to reduce its number of servers because AWS optimizes the server sizing to run the existing functions. Even after beginning operation, ANA has continued stable operation using AWS's enterprise support to solve problems.

Amazon Redshift currently stores ANA’s international and domestic flight reservations, ticket issuing and boarding information, aircraft operation records, and cargo transportation records. Divisions of ANA--including business planning, operation quality management, and marketing--combine data on Amazon Redshift, external data, and others to analyze correlation and create reports for each purpose. Analysis performance has been improved since shifting to Amazon Redshift, with faster response and better usability for heavy users.

The move to AWS also helped ANA resolve its issues with disk capacity, batch-processing times, and load on operation processes.

"With on-premises it took three to five months to procure a server, but since AWS can launch a virtual server with just a few clicks, the lead time for procurement has been shortened to less than two months. We improved the performance of batch processing up to a factor of 100, allowing us to drastically shorten individual processing times. As a result, the system operation load of the IT department is reduced, and human resources are being allocated to more valuable tasks. With AWS, recovery is fast even if downtime occurs; having no direct effect on the work and services of ANA is extremely beneficial," says Ishii.

Through the migration to AWS, hardware-update costs have leveled out, and the company has converted its cost structure for infrastructure from fixed to variable.

In the future, ANA is considering introducing Amazon Redshift Spectrum, which can directly reference data on Amazon S3. This eliminates the need for the intermediate processing of aggregated data, leading to further improvements in performance by simplifying processing. The company also plans to actively transfer Amazon Redshift's node type to higher-performance services.

“In order to further evolve our service, I would like to continue to incorporate the knowledge of AWS, and expand and deepen its areas of application," says Fudeshima.

Hajime Fudeshima

Naoki Ishii

To learn more about how AWS can help with big-data analysis, visit our Big Data on AWS details page.